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Research Article
 

Long-term Investment Planning Model for Power Generation Capacity Based on Harmony Search Algorithm with Particle Swarm Optimization



Chai Dapeng, Ma Mingjuan, Xue Song, Shi Hui and Zeng Ming
 
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ABSTRACT

Under the condition of large-scale renewable energy integrated into grid, optimizing generation capacity investment needs to achieve large-scale renewable energy integrated into grid and to take into account the economic and environmental benefits. In view of the long-standing problem of uncoordinated power generation capacity investment, firstly, this study built a planning model of long-term investment in generation capacity based on minimized investment costs and minimized CO2 emissions. Secondly, the mechanism and procedure of harmony search algorithm with particle swarm optimization was introduced. Finally, the impact of different hydropower capacity and wind power capacity on portfolio investment cost of generation capacity and CO2 emissions were analyzed combined with scenario simulations. In addition, long-term investment planning program of generation capacity was optimized in both economic and environmental benefits aspects. From the study results, it can be seen that the total cost is 2027421.34 and 158141.04 Yuan in R0 and R9 of the wet season scenario and the total CO2 emissions is 208.43 and 70.62 in R0 and R9 of the wet season scenario; the total cost is 158723.56 and 206782.12 Yuan in S0 and S9 of the dry season scenario and the total CO2 emissions is 218.91 and 74.74 in S0 and S9 of the dry season scenario. Based on this, complementary operation and optimization investment of hydro-thermal power-wind power was achieved. This study will provide a theoretical reference for policy makers.

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  How to cite this article:

Chai Dapeng, Ma Mingjuan, Xue Song, Shi Hui and Zeng Ming, 2013. Long-term Investment Planning Model for Power Generation Capacity Based on Harmony Search Algorithm with Particle Swarm Optimization. Journal of Applied Sciences, 13: 3584-3588.

DOI: 10.3923/jas.2013.3584.3588

URL: https://scialert.net/abstract/?doi=jas.2013.3584.3588
 

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